AlphaFold-Multimer accurately captures interactions and dynamics of intrinsically disordered protein regions

Proceedings of the National Academy of Sciences, Год журнала: 2024, Номер 121(44)

Опубликована: Окт. 24, 2024

Interactions mediated by intrinsically disordered protein regions (IDRs) pose formidable challenges in structural characterization. IDRs are highly versatile, capable of adopting diverse structures and engagement modes. Motivated recent strides structure prediction, we embarked on exploring the extent to which AlphaFold-Multimer can faithfully reproduce intricacies interactions involving IDRs. To this end, gathered multiple datasets covering versatile spectrum IDR binding modes used them probe AlphaFold-Multimer’s prediction their dynamics. Our analyses revealed that is not only predicting various types bound with high success rate, but distinguishing true from decoys, unreliable predictions accurate ones achievable appropriate use intrinsic scores. We found quality drops for more heterogeneous, fuzzy interaction types, most likely due lower interface hydrophobicity higher coil content. Notably though, certain scores, such as Predicted Aligned Error residue-ipTM, correlated heterogeneity IDR, enabling clear distinctions between homogeneous Finally, our benchmarking also be successful when using full-length proteins, cognate facilitate identification a given partner, established “minD,” pinpoints potential sites protein. study demonstrates correctly identify interacting predict mode partner.

Язык: Английский

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Peptide design to control protein–protein interactions

Chemical Society Reviews, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Targeting of protein–protein interactions has become huge interest in every aspect medicinal and biological sciences.

Язык: Английский

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High-throughput discovery of inhibitory protein fragments with AlphaFold

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(6)

Опубликована: Фев. 3, 2025

Peptides can bind to specific sites on larger proteins and thereby function as inhibitors regulatory elements. Peptide fragments of are particularly attractive for achieving these functions due their inherent potential form native-like binding interactions. Recently developed experimental approaches allow high-throughput measurement protein fragment inhibitory activity in living cells. However, it has thus far not been possible predict de novo which the many targets, let alone act inhibitors. We have a computational method, FragFold, that employs AlphaFold full-length manner. Applying FragFold thousands tiling across diverse revealed peaks predicted along each sequence. Comparisons with measurements establish our approach is sensitive predictor function: Evaluating from known protein–protein interaction interfaces, we find 87% by mode. Across full sequences, 68% FragFold-predicted match experimentally measured peaks. Deep mutational scanning experiments support modes uncover superior peptides high throughput. Further, able previously unknown modes, explaining prior genetic biochemical data. The success rate demonstrates this should be broadly applicable discovering proteomes.

Язык: Английский

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AlphaFold2 SLiM screen for LC3-LIR interactions in autophagy

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Сен. 10, 2024

Abstract In selective autophagy, cargo recruitment is mediated by LC3-interacting regions (LIRs) / Atg8-interacting motifs (AIMs) in the or receptor proteins. The binding of these to LC3/Atg8 proteins at phagophore membrane often modulated post-translational modifications, especially phosphorylation. As a challenge for computational LIR predictions, sequences may contain short canonical (W/F/Y)XX(L/I/V) motif without being functional. Conversely, LIRs be formed non-canonical but functional sequence motifs. AlphaFold2 has proven useful even if some are missed and with thousands residues reach limits feasibility. We present fragment-based approach address limitations. find that fragment length phosphomimetic mutations modulate interactions predicted AlphaFold2. Systematic screening range target yields structural models AlphaFold3 fail predict full-length targets. provide guidance on choice, tuning, LC3 isoform effects optimal screens. Finally, we also test transferability this general framework SUMO-SIM interactions, another type protein-protein interaction involving linear (SLiMs).

Язык: Английский

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